Application and optimization of neural field dynamics for driver assistance

Behavior planning of a vehicle in real-world traffic is a difficult problem. Complex systems have to be build to accomplish the projection of tasks, environmental constraints, and purposes of the driver to the dynamics of two controlled variables: steering angle and velocity. This paper comprises two parts. First, the behavior planning for the task of intelligent cruise control is proposed. The controlled variables are determined by evaluating the dynamics of two one-dimensional neural fields. The information concerning the actual situation and driver preferences is coupled additively into the field. Second, the parameters of the dynamics for the steering angle are adjusted by a state-of-the-art evolution strategy in order to achieve a smooth, comfortable trajectory. The behavior of the vehicle is successfully controlled by the neural field dynamics in the testbed of a simulation environment